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Collaborating Authors

 Zhao, Dengji


Coalitional Games with Stochastic Characteristic Functions and Private Types

arXiv.org Artificial Intelligence

The research on coalitional games has focused on how to share the reward among a coalition such that players are in-centivised to collaborate together. It assumes that the (deterministic or stochastic) characteristic function is known in advance. This paper studies a new setting (a task allocation problem) where the characteristic function is not known and it is controlled by some private information from the players. Hence, the challenge here is twofold: (i) incentivize players to reveal their private information truthfully, (ii) incentivize them to collaborate together. We show that existing reward distribution mechanisms or auctions cannot solve the challenge. Hence, we propose the very first mechanism for the problem from the perspective of both mechanism design and coalitional games.


Redistribution Mechanism Design on Networks

arXiv.org Artificial Intelligence

Redistribution mechanisms have been proposed for more efficient resource allocation but not for profit. We consider redistribution mechanism design for the first time in a setting where participants are connected and the resource owner is only aware of her neighbours. In this setting, to make the resource allocation more efficient, the resource owner has to inform the others who are not her neighbours, but her neighbours do not want more participants to compete with them. Hence, the goal is to design a redistribution mechanism such that participants are incentivized to invite more participants and the resource owner does not earn or lose much money from the allocation. We first show that existing redistribution mechanisms cannot be directly applied in the network setting to achieve the goal. Then we propose a novel network-based redistribution mechanism such that all participants in the network are invited, the allocation is more efficient and the resource owner has no deficit. Introduction The problem of resource allocation has recently caught the public imagination, where the resource owner has to decide the allocation of the item among a group of self-interested agents. Since the valuation differs from agents, it is a natural objective for the owner to pursue the efficiency of the allocation, i.e., allocating the item to the agent with the highest valuation. In many scenarios, the owner does not really aim at making profits but hopes the wealth maintained among the agents. For example, the government wants to build a library in a community that values it most; a charity distributes a donation to the recipient who needs it most; a hospital allocates doctors to rural areas where doctors are highly demanded. To find the agent with the highest valuation, one common alternative is to hold an auction (Krishna 2009) under some protocols such as the well-known Vickrey-Clarke- Groves (VCG) mechanism (Vickrey 1961; Clarke 1971; Groves 1973). However, the payments under VCG will all be delivered to the auctioneer, which againsts our nonprofit purpose.


Fixed-price Diffusion Mechanism Design

arXiv.org Artificial Intelligence

We consider a fixed-price mechanism design setting where a seller sells one item via a social network, but the seller can only directly communicate with her neighbours initially. Each other node in the network is a potential buyer with a valuation derived from a common distribution. With a standard fixed-price mechanism, the seller can only sell the item among her neighbours. To improve her revenue, she needs more buyers to join in the sale. To achieve this, we propose the very first fixed-price mechanism to incentivize the seller's neighbours to inform their neighbours about the sale and to eventually inform all buyers in the network to improve seller's revenue. Compared with the existing mechanisms for the same purpose, our mechanism does not require the buyers to reveal their valuations and it is computationally easy. More importantly, it guarantees that the improved revenue is at least 1/2 of the optimal.


Selling Multiple Items via Social Networks

arXiv.org Artificial Intelligence

We consider a market where a seller sells multiple units of a commodity in a social network. Each node/buyer in the social network can only directly communicate with her neighbours, i.e. the seller can only sell the commodity to her neighbours if she could not find a way to inform other buyers. In this paper, we design a novel promotion mechanism that incentivizes all buyers, who are aware of the sale, to invite all their neighbours to join the sale, even though there is no guarantee that their efforts will be paid. While traditional sale promotions such as sponsored search auctions cannot guarantee a positive return for the advertiser (the seller), our mechanism guarantees that the seller's revenue is better than not using the advertising. More importantly, the seller does not need to pay if the advertising is not beneficial to her.


Customer Sharing in Economic Networks with Costs

arXiv.org Artificial Intelligence

In an economic market, sellers, infomediaries and customers constitute an economic network. Each seller has her own customer group and the seller's private customers are unobservable to other sellers. Therefore, a seller can only sell commodities among her own customers unless other sellers or infomediaries share her sale information to their customer groups. However, a seller is not incentivized to share others' sale information by default, which leads to inefficient resource allocation and limited revenue for the sale. To tackle this problem, we develop a novel mechanism called customer sharing mechanism (CSM) which incentivizes all sellers to share each other's sale information to their private customer groups. Furthermore, CSM also incentivizes all customers to truthfully participate in the sale. In the end, CSM not only allocates the commodities efficiently but also optimizes the seller's revenue.


Mechanism Design in Social Networks

AAAI Conferences

This paper studies an auction design problem for a seller to sell a commodity in a social network, where each individual (the seller or a buyer) can only communicate with her neighbors. The challenge to the seller is to design a mechanism to incentivize the buyers, who are aware of the auction, to further propagate the information to their neighbors so that more buyers will participate in the auction and hence, the seller will be able to make a higher revenue. We propose a novel auction mechanism, called information diffusion mechanism (IDM), which incentivizes the buyers to not only truthfully report their valuations on the commodity to the seller, but also further propagate the auction information to all their neighbors. In comparison, the direct extension of the well-known Vickrey-Clarke-Groves (VCG) mechanism in social networks can also incentivize the information diffusion, but it will decrease the seller's revenue or even lead to a deficit sometimes. The formalization of the problem has not yet been addressed in the literature of mechanism design and our solution is very significant in the presence of large-scale online social networks.


Balanced Trade Reduction for Dual-Role Exchange Markets

AAAI Conferences

In designing an exchange mechanism, it is important to Exchange markets (aka double auctions) are the most important achieve a number of desirable properties, namely: maximizing institutions for modern economy, which are centralized social welfare (i.e., efficient), preventing manipulations markets consisting of exchange rules for traders to buy and of agents (i.e., truthful), an agent never pays more sell commodities, e.g. stock exchanges. Most existing studies than what she gets (i.e., individually rational) and the market of exchanges are for the environments where a trader maker should not run the mechanism with a deficit (i.e., is either a buyer or a seller, but not both, of certain commodities budget balanced). It is well known that designing an exchange (Myerson and Satterthwaite 1983; McAfee 1992; mechanism that is efficient, truthful, individually rational Wurman, Walsh, and Wellman 1998; Blum, Sandholm, and and budget balanced is impossible (Myerson and Satterthwaite Zinkevich 2006; Bredin, Parkes, and Duong 2007; Parsons, 1983). Since a loss-making mechanism does not Rodriguez-Aguilar, and Klein 2011).